Overview of Artificial Intelligence and Expert Systems: The concept and importance of AI, General Concepts of Expert System

 

Artificial Neural Networks: Artificial Neuron models, Types of activation functions, Neural network architectures, Neural Learning: Correlation, Competitive, Feedback based weight adaptation, Evaluation of networks, Quality of results, Generalizability, Computational resources, Supervised learning: Perceptrons, linear separability, Multilayer networks, Backpropagation algorithm and its varianta, Unsupervised learning, Winner-take all networks, Adaptive resonance theory, Self organizing maps, Hopfield networks, Boltzman  machines, Support Vector Machine, Typical application in identification, Optimization, Pattern recognition etc.

 

Fuzzy Logic: Fuzziness vs probability, Crisp logic vs fuzzy logic, Fuzzy sets and systems, Operations on sets, Fuzzy relations, Membership functions, Fuzzy rule generation, De fuzzy controllers, Type-2 Fuzzy Logic Controllers, Multi-layer and other advanced Fuzzy Logic Models, Applications of Fuzzy Logic.

 

Evolutionary Computation:  Introduction and concept as a process modeling tool, Genetic Algorithms and its Operators, Binary Coded Genetic Algorithm and its use in Engineering Process Modeling, Unimodal vs Multimodal problems in GA and their significance, Applications.

 

Hybrid Techniques: Neuro-fuzzy systems, Fuzzy-Expert system, Fuzzy-GA systems

 

Applications: Applications of Intelligent techniques in Process control, Robotics and other industrial control methods.

 

Laboratory Work: Experiments around Input and output using Fuzzy logic, Graphical analysis of various control systems using Fuzzy logic, Dynamical and optimal training for neural networks, Experiments around GA.

 

Recommended Books

1. Narayana, Y., Artificial Neural Networks, Prentice-Hall of India (1999).
2. Rich, E., and Knight, K., Artificial intelligence, McGraw Hill (1991) 2^nd ed.
3. Ross, J. T., Fuzzy Logic with Engineering Applications, John Wiley (2004) 2^nd ed.